Abstract
AbstractThree-dimensional image analyses are required to improve the understanding of the regulation of blood vessel formation and heterogeneity. Currently, quantitation of 3D endothelial structures or vessel branches is often based on 2D projections of the images losing their volumetric information. Here, we developed SproutAngio, a Python-based open-source tool, for fully automated 3D segmentation and analysis of endothelial lumen space and sprout morphology. To test the SproutAngio, we produced a publicly available in vitro fibrin bead assay dataset with a gradually increasing VEGF-A concentration (https://doi.org/10.5281/zenodo.7240927). We demonstrate that our automated segmentation and sprout morphology analysis, including sprout number, length, and nuclei number, outperform the widely used ImageJ plugin. We also show that SproutAngio allows a more detailed and automated analysis of the mouse retinal vasculature in comparison to the commonly used radial expansion measurement. In addition, we provide two novel methods for automated analysis of endothelial lumen space: (1) width measurement from tip, stalk and root segments of the sprouts and (2) paired nuclei distance analysis. We show that these automated methods provided important additional information on the endothelial cell organization in the sprouts. The pipelines and source code of SproutAngio are publicly available (https://doi.org/10.5281/zenodo.7381732).
Funder
EC | Horizon 2020 Framework Programme
Academy of Finland
Publisher
Springer Science and Business Media LLC
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献